CAFA-evaluator: A Python Tool for Benchmarking Ontological Classification Methods
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arXiv
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| Autori principali: | , , , , , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| _version_ | 1866916156306096128 |
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| author | Piovesan, Damiano Zago, Davide Joshi, Parnal Kaluza, M. Clara De Paolis Mehdiabadi, Mahta Ramola, Rashika Monzon, Alexander Miguel Reade, Walter Friedberg, Iddo Radivojac, Predrag Tosatto, Silvio C. E. |
| author_facet | Piovesan, Damiano Zago, Davide Joshi, Parnal Kaluza, M. Clara De Paolis Mehdiabadi, Mahta Ramola, Rashika Monzon, Alexander Miguel Reade, Walter Friedberg, Iddo Radivojac, Predrag Tosatto, Silvio C. E. |
| contents | We present CAFA-evaluator, a powerful Python program designed to evaluate the performance of prediction methods on targets with hierarchical concept dependencies. It generalizes multi-label evaluation to modern ontologies where the prediction targets are drawn from a directed acyclic graph and achieves high efficiency by leveraging matrix computation and topological sorting. The program requirements include a small number of standard Python libraries, making CAFA-evaluator easy to maintain. The code replicates the Critical Assessment of protein Function Annotation (CAFA) benchmarking, which evaluates predictions of the consistent subgraphs in Gene Ontology. Owing to its reliability and accuracy, the organizers have selected CAFA-evaluator as the official CAFA evaluation software. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_06881 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | CAFA-evaluator: A Python Tool for Benchmarking Ontological Classification Methods Piovesan, Damiano Zago, Davide Joshi, Parnal Kaluza, M. Clara De Paolis Mehdiabadi, Mahta Ramola, Rashika Monzon, Alexander Miguel Reade, Walter Friedberg, Iddo Radivojac, Predrag Tosatto, Silvio C. E. Quantitative Methods Performance We present CAFA-evaluator, a powerful Python program designed to evaluate the performance of prediction methods on targets with hierarchical concept dependencies. It generalizes multi-label evaluation to modern ontologies where the prediction targets are drawn from a directed acyclic graph and achieves high efficiency by leveraging matrix computation and topological sorting. The program requirements include a small number of standard Python libraries, making CAFA-evaluator easy to maintain. The code replicates the Critical Assessment of protein Function Annotation (CAFA) benchmarking, which evaluates predictions of the consistent subgraphs in Gene Ontology. Owing to its reliability and accuracy, the organizers have selected CAFA-evaluator as the official CAFA evaluation software. |
| title | CAFA-evaluator: A Python Tool for Benchmarking Ontological Classification Methods |
| topic | Quantitative Methods Performance |
| url | https://arxiv.org/abs/2310.06881 |